






"""simple docstring"""





def 	lowerCamelCase__			(				_lowerCamelCase			:						int					) ->							int:
  lowerCamelCase_       	=		1
  for i in range(1						,							num + 1					):
    fact *= i
  return fact







def 	lowerCamelCase__			(				_lowerCamelCase			:						int					) ->							int:
  lowerCamelCase_       	=		0
  while number > 0:
    lowerCamelCase_       	=		number % 10
    sum_of_digits += last_digit
    lowerCamelCase_       	=		number // 10  # Removing the last_digit from the given number
  return sum_of_digits







def 	lowerCamelCase__			(				_lowerCamelCase			:						int = 100					) ->							int:
  lowerCamelCase_       	=		factorial(_lowerCamelCase					)
  lowerCamelCase_       	=		split_and_add(_lowerCamelCase					)
  return result


if __name__ == "__main__":
  print(solution(int(input('''Enter the Number: ''').strip())))












"""simple docstring"""





from typing import TYPE_CHECKING

from ...utils import (
    OptionalDependencyNotAvailable,
    _LazyModule,
    is_sentencepiece_available,
    is_tokenizers_available,
    is_torch_available,
)


_SCREAMING_SNAKE_CASE   :							List[Any]          =		{'''configuration_plbart''': ['''PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP''', '''PLBartConfig''']}

try:
  if not is_sentencepiece_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							Union[str, Any]          =		['''PLBartTokenizer''']

try:
  if not is_torch_available():
    raise OptionalDependencyNotAvailable()
except OptionalDependencyNotAvailable:
  pass
else:
  _SCREAMING_SNAKE_CASE   :							List[str]          =		[
      '''PLBART_PRETRAINED_MODEL_ARCHIVE_LIST''',
      '''PLBartForCausalLM''',
      '''PLBartForConditionalGeneration''',
      '''PLBartForSequenceClassification''',
      '''PLBartModel''',
      '''PLBartPreTrainedModel''',
  ]


if TYPE_CHECKING:
  from .configuration_plbart import PLBART_PRETRAINED_CONFIG_ARCHIVE_MAP, PLBartConfig

  try:
    if not is_sentencepiece_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .tokenization_plbart import PLBartTokenizer

  try:
    if not is_torch_available():
      raise OptionalDependencyNotAvailable()
  except OptionalDependencyNotAvailable:
    pass
  else:
    from .modeling_plbart import (
        PLBART_PRETRAINED_MODEL_ARCHIVE_LIST,
        PLBartForCausalLM,
        PLBartForConditionalGeneration,
        PLBartForSequenceClassification,
        PLBartModel,
        PLBartPreTrainedModel,
    )


else:
  import sys

  _SCREAMING_SNAKE_CASE   :							Optional[Any]          =		_LazyModule(__name__, globals()['''__file__'''], _import_structure)




